Eye Detection with OpenCV
-
Eye detection is a popular and useful operation in OpenCV.
-
It can be used in a variety of applications including face recognition systems and driver fatigue detection.
-
This process use Haar cascades machine learning technique.
-
We can also use self trained models in this process.
In this tutorial, we’ll learn about eye detection with OpenCV.
Input:
Code:
import cv2
input_image = cv2.imread('gg.jpg')
eyeCascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_eye_tree_eyeglasses.xml")
gray = cv2.cvtColor(input_image, cv2.COLOR_BGR2GRAY)
eye = eyeCascade.detectMultiScale(gray)
for (x, y, w, h) in eye:
img = cv2.rectangle(input_image, (x, y), (x + w, y + h), (0, 0, 255), 2)
cv2.imshow('Detected eyes', input_image)
cv2.waitKey(0)
-
First we imported cv2 and used cv2.imread function to read the image.
-
The next line loads the pre-trained eye detection classifier.
-
Then, we used cv2.cvtcolor() function to convert input image into grayscale.
-
Then, we used eyeCascade.detectMultiScale() function to detect all the eyes in image.
-
Then, we used a for loop to draw a rectangle around the detected eyes.
-
At last, we used imshow() function to display the final result.
Result:
